About the job
Join Us in Shaping the Future
At Intersnack, data is at the heart of our decision-making process. As a Data Scientist & ML Engineer, you will play a pivotal role in transforming complex data narratives into informed business strategies. You will create predictive, prescriptive, and optimization models that empower our teams in procurement, manufacturing, and sales. By collaborating closely with AI engineers and data engineers, you’ll integrate your models into the evolving frameworks of knowledge and agentic AI at Intersnack, blending traditional machine learning techniques with the innovative capabilities of large language models and intelligent agents. We are dedicated to cultivating our talent as we expand our technological prowess, offering you a unique opportunity to influence how AI reasoning is integrated into a global enterprise.
What We Offer
In this role, you will tackle a diverse array of modeling challenges that have significant commercial implications, from demand forecasting and process optimization to procurement analytics and scenario modeling. You will have direct access to key business stakeholders who will rely on your models to guide their decisions. Your work will not remain theoretical; it will be operationalized, monitored, and continuously refined within production environments. Collaborating with AI architects and engineers, you will embed predictive analytics into agentic workflows, amplifying the impact of your models beyond individual applications. Based in Düsseldorf, this position offers flexible remote work options, and Intersnack's global presence ensures your models will be deployed at scale.
Your Role as Our Data Scientist & ML Engineer
You will allocate your time between developing innovative models and enhancing existing ones, while also integrating machine learning outputs into analytical and agentic systems. Furthermore, you will actively engage with business stakeholders to help them understand and trust the results generated by your models. Your work will seamlessly bridge technical statistical modeling and ML engineering with the business objectives of a company that seeks to extract tangible, measurable value from AI.
Key Responsibilities
Develop, validate, and deploy a variety of predictive, prescriptive, and optimization models focusing on procurement, manufacturing, and sales to convert data into actionable insights and strategic recommendations.
Construct, refine, and adapt large language models (LLMs) and specialized models tailored for business-specific NLP tasks, including analysis of unstructured data.
